How to build a UX research system that runs on autopilot

UX research allows you to test and validate your hypotheses by understanding how people are using your product. It’s cheaper and more efficient to talk to your users before starting to write code.

But to really get into your users’ heads, you can’t simply schedule user sessions and interviews every time you’re about to launch a new product or feature. Today, products must rapidly adapt to the needs of their users or die quickly.

Quantitative metrics will always give you lagging indicators but won’t tell you how to think about your product holistically.

As Arjun Sethi, founder of MessageMe and a partner at Social Capital, writes: Your customers are consuming an experience. How do you test, ask questions and synthesize that information? How do you think about your product over the course of a few weeks to a few years and evolve it? It’s tempting to think about just the initial numbers but it’s better to focus on the entire experience. Quantitative metrics will always give you lagging indicators but won’t tell you how to think about your product holistically.

The ability to rapidly synthesize qualitative data from your users and build your product accordingly gives you the superpower of being able to move faster than the competition.

But when you’re working with a small team and limited resources, it can be difficult to make time for UX research — you’re too busy putting out fires, dealing with customer concerns, squashing bugs, and building out your product.

To get the user insights you need to improve, you need to set up a system where your team is constantly receiving a steady stream of quality user feedback. You don’t need a big UX research team or a massive budget to achieve this. By automating your UX workflow, you can spend less time on the logistics of UX research — finding users to talk to, scheduling interviews — and more time getting into the heads of your users.

Here’s a step-by-step guide for automating your UX research flow to make sure you’re receiving a steady stream of user feedback throughout your entire product cycle.

1. Fill up your UX funnel

UX research begins with the customer. That’s also one of the biggest barriers to creating a constant cycle of research and development. If you only talk to your users before a new feature launch, you limit your ability to continuously learn about your users.

Fortunately, your product and support teams are already getting feedback from users. Often, this type of feedback isn’t deep enough to generate the depth of user insights you need. But it provides you with a base of people that you can talk to further.

NPS surveys are particularly helpful for this because they segment your users into three distinct categories — promoters, passives, and detractors. An NPS survey has two parts:

On a scale of 0–10, how likely is it that you would recommend our product to a friend or colleague?

Why?

An NPS survey form in Airtable. You can play around with it directly in
this template.

It’s the quantitative part of the NPS survey that you want to focus on, because that gives you an easy way to segment the responses. Let’s say that for user research, you only want to talk to people who are enthusiastic promoters of your product, or unhappy detractors.

Using an event-driven email platform like Customer.io, you can send segments of users an automated email that asks them if they’d be willing to participate in user research studies.

Here’s what that looks like in Customer.io:

In the screenshot above, we’ve set up a segment in Customer.io for whenever a user answers an NPS survey with a score ≤ 1 or ≥ 9. Whenever a user enters this segment, it triggers an email that asks the user to opt-in to doing User Research.

This provides you with a base of users that you can talk to for more feedback — and one that doesn’t run dry. Every time your product or support team sends an NPS survey, you replenish your store of users to talk to.

2. Automatically schedule user sessions

If you’re running a small UX team, reaching out to each user individually can throw up a massive roadblock to your quest to learn faster. But if you don’t make the time to talk to your users, you’ll never have the time.

Once you ensure you have a steady stream of users to talk to coming in at the top of the funnel, the next step is to actually get them on a video call or on the phone. By automatically creating and scheduling sessions, you carve out more time that you can use to talk to more people and learn faster.

At Segment, an Analytics API and data platform, the team uses Customer.io, to put scheduling research interviews on autopilot. For every user who has opted into UX research, they create a custom segment in Customer.io:

They then send Calendly invites to users who have opted in, allowing them to self-schedule user sessions via video call or in-person. Calendly is a meeting scheduling tool that allows you to set aside blocks of time in your calendar showing your availability. Users can click on the invite, pick an open slot on your calendar, and flexibly choose a time.

As Eileen Ruberto, a UX Researcher at Zapier says, “I love how organized this makes me. I have this one source of truth for all the stuff I need to keep track of without having to duplicate it in multiple places.”

Try this out for yourself with Zapier and Airtable. Using Zapier, you can link Airtable to a tool like Customer.io. Each time a user opts into your user research program, you can use Zapier to pass that information from Customer.io and update an “opted-in” field in Airtable.

You won’t want to schedule a session with everyone who is willing to talk to you. Create a “Schedule User Interview” checkbox in Airtable. Using Zapier, you can automatically email users with a Calendly invite when the field is checked.

Just a couple, simple automations have the power to bring you closer to your users. It eliminates the grunt work of scheduling and logistics, freeing up your time to actually talk to people.

3. Accelerate learning from feedback

Once the user session is finished, the last step is to make sure the feedback from that session is categorized, tagged, and processed for potential insights. By instrumenting your feedback loop, you can semi-automatically enrich the feedback you receive in real-time.

At WeWork, researchers submit observations from UX research using this form.

The more you can automate your firehose of UX research, the faster you’re able to process data and metadata. Not only do you conduct UX research faster, you accelerate the pace that you learn from it.

Start by sending interviewers a form immediately before each user study begins with a field for notes where they can jot down their observations, and tag the feedback according to the relevant part of your product.

Now that the information’s categorized, it’s really simple to organize and present the data accordingly. WeWork created an Airtable base for exactly this purpose. Using Airtable to categorize and sort UX research allows the entire team — not just researchers — to benefit from research.

In an effort to democratize UX and share learnings across the team, Tomer Sharon, WeWork’s head of UX, helped build Polaris. Polaris is an internal, searchable database, that anyone at WeWork can search for research insights. The atomic unit of research at WeWork is the “nugget,” or an observation of a user insight gleaned from talking to users.

By linking observation records to specific moments in a user journey in Airtable, WeWork can automatically categorize user sessions according to observed user behavior.

When you’re starting out though, you don’t need to build your own system to share research insights across your team. Email works just as well. Because you’ve done the hard work of properly categorizing and organizing your metadata, it’s really easy to send an automated email to your team each week that summarizes research findings.

In the image above, we’ve modified WeWork’s Polaris database and created a view in Airtable with user feedback over the last month. The view is filtered by observations logged within the past month, and grouped according to a users stage in the journey.

You can pull high-level insights from this view each month and send them to your team in a monthly email digest. Team members can scan the email for high-level insights, and dive right into the research database to find out more.

More research, faster

The biggest limitation of traditional UX teams has simply been manpower. Most teams building software products can only afford to hire so many researchers, so the amount of research you could do was limited to the amount of researchers available to talk to users and synthesize their findings.

Today, software tools and automation enable researcher teams to organize, categorize, and process more data, faster. Being “user-centric” is trendy in software. But in practice, simply doing user research isn’t enough to give you a competitive edge. You have to create workflows that actually help you learn faster about your users, and iterate faster on product.